The hippocampal formation presents a special opportunity for realistic neural modeling since its structure, connectivity, and physiology are better understood than that of other cortical components. A review of the quantitative neuroanatomy of the rodent dentate gyrus (DG) is presented in the context of the development of a computational model of its connectivity. The DG is a three-layered folded sheet of neural tissue. This sheet is represented as a rectangle, having a surface area of 37 mm2 and a septotemporal length of 12 mm. Points, representing cell somata, are distributed in the model rectangle in a roughly uniform fashion. Synaptic connectivity is generated by assigning each presynaptic cell a spatial zone representing its axonal arbor. For each postsynaptic cell, a list of potential presynaptic cells is compiled, based on which arbor zones the given postsynaptic cell falls within. An appropriate number of presynaptic inputs are then selected at random. The principal cells of the DG, the granule cells, are represented in the model, as are non-principal cells, including basket cells, chandelier cells, mossy cells, and GABAergic peptidergic polymorphic (GPP) cells. The neurons of layer II of the entorhinal cortex are included also. The DG receives its main extrinsic input from these cells via the perforant path. The basket cells, chandelier cells, and GPP cells receive perforant path and granule cell input and exert both feedforward and feedback inhibition onto the granule cells. Mossy cells receive converging input from granule cells and send their output back primarily to distant septotemporal levels, where they contact both granule cells and non-principal cells. To permit numerical simulations, the model must be scaled down while preserving its anatomical structure. A variety of methods for doing this exist. Hippocampal allometry provides valuable clues in this regard.